• Journal of Drive and Control
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• v.15 no.4
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• pp.30-38
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• 2018

Electronic control units (ECUs) are currently popular, and have evolved further towards the high-end application of autonomous vehicles in the automotive industry. Such digital technologies have also become widespread, in agriculture and construction equipment. Likewise, transmission control of high-speed tracked vehicles is based on the transmission control unit (TCU), performing complex gear change control functions, and diagnostic algorithms (a TCU's self-diagnostic and reporting capability of malfunction data through CAN communication). Since all functions of TCU are implemented by embedded-software, it is hardly possible to analyze specifications by reverse engineering. In this paper a real-time transmission simulator adaptable to TCU is presented, for analysis of diagnosis algorithm and standards. Signal simulation circuits are deliberately designed considering electrical characteristics of TCU inputs and various analysis tools, such as analog input auto scan function, and global output enable switch, are implemented in software. Test results from hardware-in-the-loop simulator verify tolerance time for each error, as well as cause of fault, error reset conditions.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.457-466
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• 2021

This paper describes the design of model-based fault diagnosis software to apply to the propulsion system in tracked amphibious assault vehicle which consists of an engine, a transmission, a cooling system, and two waterjets. This software includes specific functions to detect the failures regarding sensor malfunctions, mechanical malfunctions, control errors, and communication errors. This software generates the proper malfunction codes which are classified as the warning and caution. In order to validate the fault diagnosis software, the manual and automatic test are performed using the test program with 32 test cases. Test results show that the designed fault diagnosis software is reliable and effective for applying to the propulsion system.

• Design & Manufacturing
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• v.16 no.4
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.61-68
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• 2001

A rotor system is composed of a rotating shaft with supporting bearings. The rotor system is widely used in every rotating machinery such as the turbine generator and the high precision machine tools. A negligible error or malfunction in the rotor, however, can cause a catastrophic failure in the system then result in the environmental and economic disasters. A diagnosis of the rotor system is important in preventing these kinds of failures and disasters. Up to now, many researchers have devoted in the development of diagnosing tools for the system. The basic principles behind the tools are to retrieve the data through the sensors for a specific state of the system and then to identify the specific state through the heuristic methods such as neural network, fuzzy logic, and decision matrix. The proper usage of the heuristic methods will enhance the performance of the diagnostic procedure when together used with the statistical signal processing. In this paper, the methodologies in using the above 3 heuristic methods for the diagnostics of the rotor system are established and also tested and validated for the data retrieved from the rolling element bearing and journal bearing supported system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.47-55
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• 2015

To verify the function of vehicle is becoming more and more difficult because many electronic control units have been embedded in vehicle with development of electronics industry. The reliability of vehicle should be considered above all important because malfunction of vehicle can cause damage of human life. In this paper, defect diagnosis platform based on CAN network is proposed to improve the reliability of vehicle. Reliability of vehicle is significantly increased by adopting the structural test via dedicated test path after manufacturing. Besides, the test cost is reduced because additional test pins are not required.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.28-34
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• 2021

The Fourth Industrial Revolution has led to the development of drones for commercial and private applications. Therefore, the malfunction of drones has become a prominent problem. Failure mode and effect analysis was used in this study to analyze the primary cause of drone failure, and blade breakage was observed to have the highest frequency of failure. This was tested using a vibration sensor placed on drones along the breakage length of the blades. The data exhibited a significant increase in vibration within the drone body for blade fracture length. Principal component analysis was used to reduce the data dimension and classify the state with machine learning algorithms such as support vector machine, k-nearest neighbor, Gaussian naive Bayes, and random forest. The performance of machine learning was higher than 0.95 for the four algorithms in terms of accuracy, precision, recall, and f1-score. A follow-up study on failure prediction will be conducted based on the results of fault diagnosis.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.383-388
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• 2006

SBR is one of the most general sewage/wastewater treatment processes and, particularly, has an advantage in high concentration wastewater treatment like sewage wastewater. A Kernel PCA based fault diagnosis system for biological reaction in full-scale wastewater treatment plant was proposed using only common bio-chemical sensors such as ORP(Oxidation-Reduction Potential) and DO(Dissolved Oxygen). During the SBR operation, the operation status could be divided into normal status and abnormal status such as controller malfunction, influent disturbance and instrumental trouble. For the classification and diagnosis of these statuses, a series of preprocessing, dimension reduction using PCA, LDA, K-PCA and feature reduction was performed. Also, the diagnosis result using differential data was superior to that of raw data, and the fusion data show better results than other data. Also, the results of combination of K-PCA and LDA were better than those of LDA or (PCA+LDA). Finally, the fault recognition rate in case of using only ORP or DO was around maximum 97.03% and the fusion method showed better result of maximum 98.02%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4576-4582
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• 2010

Because most of vehicle provide users with the very limited information regarding the performance of vehicle, it is quite difficult for users to drive vehicles safe, and to maintain and repair vehicles properly. In order to solve the above-mentioned problems, several ways of research and development for the vehicle control and diagnosis system have been recently carried out. However, a lot of complicated problems and difficulties were arising due to the complexity of the developed system, degradation of the reliability for the vehicle performance control system, operational malfunction and so on. In this paper, for the purpose of solving the difficult problems and technical limitations, a system for vehicle performance which might be able to diagnose the reliability of vehicle performance by measuring and analyzing the real time performance of vehicle using the satellite telemetry technology was conmance oly defined and deehiced.hihe results derived from the cormance ofdvehiclactivities in this study shall be used as not only fundamental data but also materials for the detailed design for the implementation of vehicle performance diagnosis system in the near future.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1631_1632
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• 2009

일반적으로 3상 유도전동기 회로에서는 회전자계를 얻기 위하여 델타회로가 이용되고 권선의 리액턴스(xL) 성분에 의한 역률지연에 따라 컨덕턴스(xC)회로를 통하여 보상을 하는 회로를 채용하며 관련 회로는 중성선에 흐르는 전류나 전압을 통하여 제어를 한다. 이러한 제어 회로는 몇 가지 문제점이 있는데 델타회로에서는 중성선이 없어 제어가 불가능하고, 실제로 사고 시 현존하는 고속도 계전기의 동작시간인 3사이클 이전에 사고가 진행되는 경우 실제 동작이 불가능한 문제점이 제기된다. 본 논문에서는 이러한 단점을 개선하기 위해 무효전력계통에서 유효전력을 측정하여 고장 및 사고를 사전에 예방하는 방법을 제안하고 시뮬레이션을 통해 타당성을 검증한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.634-637
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• 2000

A diagnosis system that provides early warnings regarding machine malfunction is very important for rolling mill so as to avoid great losses resulting from unexpected shutdown of the production line. But it is very difficult to provide early warnings in rolling mill. Because dynamics of rolling mill is non-linear. This paper shows a chaotic behaviour of vibration signal in rolling mill using embedding method. Not only phase plane and Poincare map are implemented but also FFT and histogram of vibration signal in rolling mill is presented by embedding method.